I have a general question about Kotlin collections.
Why are there mutable versions of so many collections (like the MutableList) when we have the val vs var distinction?
Well....ok...actually, I understand that val doesn't have anything to do with the 'mutability' of the object, but rather the 're-initializability' of the object.
But then that raises the question....why isn't MutableList the default?
TL;DR
Individually, mutable and immutable collections are able to expose useful features that can't co-exist in a single interface:
Mutable collections can be read from and written to. But Kotlin strives to avoid all runtime failures, therefore, these mutable collections are invariant.
Immutable collections are covariant, but they're...well...immutable. Still, Kotlin does provide mechanisms for doing useful things with these immutable collections (like filtering values or creating new immutable collections from existing ones). You can go through the long list of convenience functions for Kotlin's (immutable) List interface for examples.
Immutable collections in Kotlin cannot have elements added or removed from them; they can only be read from. But this apparent restriction makes it possible to do some subtyping with the immutable collections. From the Kotlin docs:
The read-only collection types are covariant...the collection types have the same subtyping relationship as the element types.
This means that, if a Rectangle class is a child of a Shape class, you can place a List<Rectangle> object in a List<Shape> variable whenever required:
fun stackShapes(val shapesList: List<Shape>) {
...
}
val rectangleList = listOf<Rectangle>(...)
// This is valid!
stackShapes(rectangleList)
Mutable collections, on the other hand, can be read from and written to. Because of this, no sub-typing or super-typing is possible with them. From the Kotlin docs:
...mutable collections aren't covariant; otherwise, this would lead to runtime failures. If MutableList<Rectangle> was a subtype of MutableList<Shape>, you could insert other Shape inheritors (for example, Circle) into it, thus violating its Rectangle type argument.
val rectangleList = mutableListOf<Rectangle>(...);
val shapesList: MutableList<Shape> = rectangleList // MutableList<Rectangle>-type object in MutableList<Shape>-type variable
val circle = Circle(...)
val shape: Shape = circle // Circle-type object in Shape-type variable
// Runtime Error!
shapesList.add(shape) // You're actually trying to add a Circle to a MutableList<Rectangle>
// If rectanglesList couldn't be put into a variable with type MutableList<Shape> in the first place, you would never have run into this problem.
At this point, you might be thinking: "So what? Kotlin could just add type-checks to all of the write-methods of Mutable Collections...then you could allow them to be covariant, and you wouldn't need separate immutable collections!"
Which is true, except that it would go completely against a core Kotlin philosophy; to avoid nulls and runtime errors whenever possible. You see, the methods of such a Collection would have to return null - or raise an Exception - whenever a type-check fails. This would only become apparent at runtime, and since that can be avoided by simply making Mutable Collections invariant...that's exactly what Kotlin does.
From the Kotlin docs:
The read-only collection types are covariant. This means that, if a Rectangle class inherits from Shape, you can use a List<Rectangle> anywhere the List<Shape> is required. In other words, the collection types have the same subtyping relationship as the element types. Maps are covariant on the value type, but not on the key type.
In turn, mutable collections aren't covariant; otherwise, this would lead to runtime failures. If MutableList<Rectangle> was a subtype of MutableList<Shape>, you could insert other Shape inheritors (for example, Circle) into it, thus violating its Rectangle type argument.
To paraphrase, if it's immutable you know all the types are the same. If not, you might have different inheritors.
Related
I know what classes are about, but for better understanding I need a use case. Recently I discovered the construct of data classes. I get the idea behind normal classes, but I cannot imagine a real use case for data classes.
When should I use a data class and when I use a "normal" class? For all I know, all classes keep data.
Can you provide a good example that distinguishes data classes from non-data classes?
A data class is used to store data. It's lighter than a normal class, and can be compared to an array with key/value (dictionary, hash, etc.), but represented as an object with fixed attributes. In kotlin, according to the documentation, that adds those attributes to the class:
equals()/hashCode() pair
toString() of the form "User(name=John, age=42)"
componentN() functions corresponding to the properties in their order of declaration.
copy() function
Also it has a different behavior during class inheritence :
If there are explicit implementations of equals(), hashCode(), or toString() in the data class body or final implementations in a
superclass, then these functions are not generated, and the existing
implementations are used.
If a supertype has componentN() functions that are open and return compatible types, the corresponding functions are generated for the
data class and override those of the supertype. If the functions of
the supertype cannot be overridden due to incompatible signatures or
due to their being final, an error is reported.
Providing explicit implementations for the componentN() and copy() functions is not allowed.
So in kotlin, if you want to describe an object (a data) then you may use a dataclass, but if you're creating a complex application and your class needs to have special behavior in the constructor, with inheritence or abstraction, then you should use a normal class.
I do not know Kotlin, but in Python, a dataclass can be seen as a structured dict. When you want to use a dict to store an object which has always the same attributes, then you should not put it in a dict but use a Dataclass.
The advantage with a normal class is that you don't need to declare the __init__ method, as it is "automatic" (inherited).
Example :
This is a normal class
class Apple:
def __init__(size:int, color:str, sweet:bool=True):
self.size = size
self.color = color
self.sweet = sweet
Same class as a dataclass
from dataclasses import dataclass
#dataclass
class Apple:
size: int
color: str
sweet: bool = True
Then the advantage compared to a dict is that you are sure of what attribute it has. Also it can contains methods.
The advantage over to a normal class is that it is simpler to declare and make the code lighter. We can see that the attributes keywords (e.g size) are repeated 3 times in a normal class, but appear only once in a dataclass.
The advantage of normal class also is that you can personalize the __init__ method, (in a dataclass also, but then you lose it's main advantage I think) example:
# You need only 2 variable to initialize your class
class Apple:
def __init__(size:int, color:str):
self.size = size
self.color = color
# But you get much more info from those two.
self.sweet = True if color == 'red' else False
self.weight = self.__compute_weight()
self.price = self.weight * PRICE_PER_GRAM
def __compute_weight(self):
# ...
return (self.size**2)*10 # That's a random example
Abstractly, a data class is a pure, inert information record that doesn’t require any special handling when copied or passed around, and it represents nothing more than what is contained in its fields; it has no identity of its own. A typical example is a point in 3D space:
data class Point3D(
val x: Double,
val y: Double,
val z: Double
)
As long as the values are valid, an instance of a data class is entirely interchangeable with its fields, and it can be put apart or rematerialized at will. Often there is even little use for encapsulation: users of the data class can just access the instance’s fields directly. The Kotlin language provides a number of convenience features when data classes are declared as such in your code, which are described in the documentation. Those are useful when for example building more complex data structures employing data classes: you can for example have a hashmap assign values to particular points in space, and then be able to look up the value using a newly-constructed Point3D.
val map = HashMap<Point3D, String>()
map.set(Point3D(3, 4, 5), "point of interest")
println(map.get(Point3D(3, 4, 5))) // prints "point of interest"
For an example of a class that is not a data class, take FileReader. Underneath, this class probably keeps some kind of file handle in a private field, which you can assume to be an integer (as it actually is on at least some platforms). But you cannot expect to store this integer in a database, have another process read that same integer from the database, reconstruct a FileReader from it and expect it to work. Passing file handles between processes requires more ceremony than that, if it is even possible on a given platform. That property makes FileReader not a data class. Many examples of non-data classes will be of this kind: any class whose instances represent transient, local resources like a network connection, a position within a file or a running process, cannot be a data class. Likewise, any class where different instances should not be considered equal even if they contain the same information is not a data class either.
From the comments, it sounds like your question is really about why non-data classes exist in Kotlin and why you would ever choose not to make a data class. Here are some reasons.
Data classes are a lot more restrictive than a regular class:
They have to have a primary constructor, and every parameter of the primary constructor has to be a property.
They cannot have an empty primary constructor.
They cannot be open so they cannot be subclassed.
Here are other reasons:
Sometimes you don't want a class to have a copy function. If a class holds onto some heavy state that is expensive to copy, maybe it shouldn't advertise that it should be copied by presenting a copy function.
Sometimes you want to use an instance of a class in a Set or as Map keys without two different instances being considered as equivalent just because their properties have the same values.
The features of data classes are useful specifically for simple data holders, so the drawbacks are often something you want to avoid.
I have class that internally maintains a mutable list, and I want to provide an immutable view on this list. Currently I'm using the following:
/**The list that actually stores which element is at which position*/
private val list: MutableList<T> = ArrayList()
/**Immutable view of [list] to the outside.*/
val listView: List<T> get() = list.toList()
First question: Can this be done easier
Second question: How can I test that listView is actually immutable. I guess reflections are necessary?
If you only needed the compile-time type to be immutable, you could simply upcast your list:
val listView: List<T> get() = list
(Though if you checked and downcast that to MutableList, you could make changes — and those would affect the original list.)
However, if you want full immutability, that's tricky. I don't think there are any general-purpose truly immutable lists in the Kotlin stdlib.
Although List and MutableList look like two different types, in Kotlin/JVM they both compile down to the same type in the bytecode, which is mutable. And even in Kotlin, while Iterable.toList() does return a new list, the current implementation* actually gives a MutableList that's been upcast to List. (Though mutating it wouldn't change the original list.)
Some third-party libraries provide truly immutable collections, though; see this question.
And to check whether a List is mutable, you could use a simple type check:
if (listView is MutableList)
// …
No need to use reflection explicitly. (A type check like that is considered to be implicit reflection.)
(* That can change, of course. It's usually a mistake to read too much into the current code, if it's not backed up by the documentation.)
I need to get and set a property of another class from a method and therefore need to pass in either the property reference of lambdas for the getter and the setter:
Passing in the property reference
otherInstance::property
Passing in a lambda for the getter and one for the setter:
{otherInstance.property} // getter
{value -> otherInstance.property = value} // setter
I like the first one, because for me the code is easier to read and shorter, but my alarm bells ring when I read about it on the official documentation, because of the term "reflection". My knowledge from Java is that reflection generally isn't a good thing. Is that also valid with Kotlin? Is it valid with this case? Is one of both ways (property reference or lambdas) more performant or more safe?
By using KMutableProperty0 you would technically be exposing an object that can be used for reflection. If you want to be strict about avoiding reflection, you could use the separate function references for the getter and setter. Note that it's not necessary to pass a lambda as a function reference to a higher-order function. The compiler can interpret property references as functions if the effective signature matches. This would unfortunately mean having to pass the property reference twice. Unfortunately, the setter has to be retrieved via what is technically reflection in this case:
class Test (var x: Int)
fun foo(getter: () -> Int, setter: (Int) -> Unit) {
//...
}
val test = Test(1)
foo(test::x, test::x.setter)
// Zero reflection call:
foo(test::x) { test.x = it }
At some point you have to question how badly you want to avoid reflection, because the above code looks very messy to me. If your class takes a KMutableProperty0 reference, it is much simpler to use. As long as your receiving function isn't using the reference to introspect the code, and only calls get() or set() on it, you are not really using reflection in the ways that are suggested should be avoided.
fun foo(property: KMutableProperty0<Int>) {
//...
}
val test = Test(1)
foo(test::x)
The documentation is about Member references and reflection,
If you are referring to Property references which isn't using reflection itself,
Reflection is only referred in different section Obtaining member references from a class reference
dynamically inspect an object to see e.g. what properties and functions it contains and which annotations exist on them. This is called reflection, and it's not very performant, so avoid it unless you really need it.
Kotlin has got its own reflection library (kotlin-reflect.jar must be included in your build). When targeting the JVM, you can also use the Java reflection facilities. Note that the Kotlin reflection isn't quite feature-complete yet - in particular, you can't use it to inspect built-in classes like String.
In my software, I have some various values which use property delegation.
This is a simple similar example showing what I do:
class ExampleDelegate<T>(val value: T) {
operator fun getValue(thisRef: Any?, property: KProperty<*>) = value
}
val example by ExampleDelegate(1000) // number larger than 127 (no box cache)
What I've noticed, however, is that referring to this value seems to create an autoboxed object (java.lang.Integer) on EVERY reference. Because the value must be referenced potentially millions or times per second, this results in massive garbage creation for my software; heavy stress is put on the garbage collector.
Is there a way to avoid the overhead? If not directly, are there any clever ways to "emulate" property delegation that are performant?
Submitted a bug report on YouTrack: https://youtrack.jetbrains.com/issue/KT-13606
As discussed in the bug report, your app generates garbage because your property delegate is generic, and therefore requires boxing of values. If you use a non-generic property delegate with a primitive type, no boxing happens.
I am learning Kotlin and it is looking likely I may want to use it as my primary language within the next year. However, I keep getting conflicting research that Kotlin does or does not have immutable collections and I'm trying to figure out if I need to use Google Guava.
Can someone please give me some guidance on this? Does it by default use Immutable collections? What operators return mutable or immutable collections? If not, are there plans to implement them?
Kotlin's List from the standard library is readonly:
interface List<out E> : Collection<E> (source)
A generic ordered collection of elements. Methods in this interface
support only read-only access to the list; read/write access is
supported through the MutableList interface.
Parameters
E - the type of elements contained in the list.
As mentioned, there is also the MutableList
interface MutableList<E> : List<E>, MutableCollection<E> (source)
A generic ordered collection of elements that supports adding and
removing elements.
Parameters
E - the type of elements contained in the list.
Due to this, Kotlin enforces readonly behaviour through its interfaces, instead of throwing Exceptions on runtime like default Java implementations do.
Likewise, there is a MutableCollection, MutableIterable, MutableIterator, MutableListIterator, MutableMap, and MutableSet, see the stdlib documentation.
It is confusing but there are three, not two types of immutability:
Mutable - you are supposed to change the collection (Kotlin's MutableList)
Readonly - you are NOT supposed to change it (Kotlin's List) but something may (cast to Mutable, or change from Java)
Immutable - no one can change it (Guavas's immutable collections)
So in case (2) List is just an interface that does not have mutating methods, but you can change the instance if you cast it to MutableList.
With Guava (case (3)) you are safe from anybody to change the collection, even with a cast or from another thread.
Kotlin chose to be readonly in order to use Java collections directly, so there is no overhead or conversion in using Java collections..
As you see in other answers, Kotlin has readonly interfaces to mutable collections that let you view a collection through a readonly lens. But the collection can be bypassed via casting or manipulated from Java. But in cooperative Kotlin code that is fine, most uses do not need truly immutable collections and if your team avoids casts to the mutable form of the collection then maybe you don't need fully immutable collections.
The Kotlin collections allow both copy-on-change mutations, as well as lazy mutations. So to answer part of your questions, things like filter, map, flatmap, operators + - all create copies when used against non lazy collections. When used on a Sequence they modify the values as the collection as it is accessed and continue to be lazy (resulting in another Sequence). Although for a Sequence, calling anything such as toList, toSet, toMap will result in the final copy being made. By naming convention almost anything that starts with to is making a copy.
In other words, most operators return you the same type as you started with, and if that type is "readonly" then you will receive a copy. If that type is lazy, then you will lazily apply the change until you demand the collection in its entirety.
Some people want them for other reasons, such as parallel processing. In those cases, it might be best to look at really high performance collections designed just for those purposes. And only use them in those cases, not in all general cases.
In the JVM world it is hard to avoid interop with libraries that want standard Java collections, and converting to/from these collections adds a lot of pain and overhead for libraries that do not support the common interfaces. Kotlin gives a good mix of interop and lack of conversion, with readonly protection by contract.
So if you can't avoid wanting immutable collections, Kotlin easily works with anything from the JVM space:
Guava (https://github.com/google/guava)
Dexx a port of the Scala collections to Java (https://github.com/andrewoma/dexx) with Kotlin helpers (https://github.com/andrewoma/dexx/blob/master/kollection/README.md)
Eclipse Collections (formerly GS-Collections) a really high performance, JDK compatible, top performer in parallel processing with immutable and mutable variations (home: https://www.eclipse.org/collections/ and Github: https://github.com/eclipse/eclipse-collections)
PCollections (http://pcollections.org/)
Also, the Kotlin team is working on Immutable Collections natively for Kotlin, that effort can be seen here:
https://github.com/Kotlin/kotlinx.collections.immutable
There are many other collection frameworks out there for all different needs and constraints, Google is your friend for finding them. There is no reason the Kotlin team needs to reinvent them for its standard library. You have a lot of options, and they specialize in different things such as performance, memory use, not-boxing, immutability, etc. "Choice is Good" ... therefore some others: HPCC, HPCC-RT, FastUtil, Koloboke, Trove and more...
There are even efforts like Pure4J which since Kotlin supports Annotation processing now, maybe can have a port to Kotlin for similar ideals.
Kotlin 1.0 will not have immutable collections in the standard library. It does, however, have read-only and mutable interfaces. And nothing prevents you from using third party immutable collection libraries.
Methods in Kotlin's List interface "support only read-only access to the list" while methods in its MutableList interface support "adding and removing elements". Both of these, however, are only interfaces.
Kotlin's List interface enforces read-only access at compile-time instead of deferring such checks to run-time like java.util.Collections.unmodifiableList(java.util.List) (which "returns an unmodifiable view of the specified list... [where] attempts to modify the returned list... result in an UnsupportedOperationException." It does not enforce immutability.
Consider the following Kotlin code:
import com.google.common.collect.ImmutableList
import kotlin.test.assertEquals
import kotlin.test.assertFailsWith
fun main(args: Array<String>) {
val readOnlyList: List<Int> = arrayListOf(1, 2, 3)
val mutableList: MutableList<Int> = readOnlyList as MutableList<Int>
val immutableList: ImmutableList<Int> = ImmutableList.copyOf(readOnlyList)
assertEquals(readOnlyList, mutableList)
assertEquals(mutableList, immutableList)
// readOnlyList.add(4) // Kotlin: Unresolved reference: add
mutableList.add(4)
assertFailsWith(UnsupportedOperationException::class) { immutableList.add(4) }
assertEquals(readOnlyList, mutableList)
assertEquals(mutableList, immutableList)
}
Notice how readOnlyList is a List and methods such as add cannot be resolved (and won't compile), mutableList can naturally be mutated, and add on immutableList (from Google Guava) can also be resolved at compile-time but throws an exception at run-time.
All of the above assertions pass with exception of the last one which results in Exception in thread "main" java.lang.AssertionError: Expected <[1, 2, 3, 4]>, actual <[1, 2, 3]>. i.e. We successfully mutated a read-only List!
Note that using listOf(...) instead of arrayListOf(...) returns an effectively immutable list as you cannot cast it to any mutable list type. However, using the List interface for a variable does not prevent a MutableList from being assigned to it (MutableList<E> extends List<E>).
Finally, note that an interface in Kotlin (as well as in Java) cannot enforce immutability as it "cannot store state" (see Interfaces). As such, if you want an immutable collection you need to use something like those provided by Google Guava.
See also ImmutableCollectionsExplained · google/guava Wiki · GitHub
NOTE: This answer is here because the code is simple and open-source and you can use this idea to make your collections that you create immutable. It is not intended only as an advertisement of the library.
In Klutter library, are new Kotlin Immutable wrappers that use Kotlin delegation to wrap a existing Kotlin collection interface with a protective layer without any performance hit. There is then no way to cast the collection, its iterator, or other collections it might return into something that could be modified. They become in effect Immutable.
Klutter 1.20.0 released which adds immutable protectors for existing collections, based on a SO answer by #miensol provides a light-weight delegate around collections that prevents any avenue of modification including casting to a mutable type then modifying. And Klutter goes a step further by protecting sub collections such as iterator, listIterator, entrySet, etc. All of those doors are closed and using Kotlin delegation for most methods you take no hit in performance. Simply call myCollection.asReadonly() (protect) or myCollection.toImmutable() (copy then protect) and the result is the same interface but protected.
Here is an example from the code showing how simply the technique is, by basically delegating the interface to the actual class while overriding mutation methods and any sub-collections returned are wrapped on the fly.
/**
* Wraps a List with a lightweight delegating class that prevents casting back to mutable type
*/
open class ReadOnlyList <T>(protected val delegate: List<T>) : List<T> by delegate, ReadOnly, Serializable {
companion object {
#JvmField val serialVersionUID = 1L
}
override fun iterator(): Iterator<T> {
return delegate.iterator().asReadOnly()
}
override fun listIterator(): ListIterator<T> {
return delegate.listIterator().asReadOnly()
}
override fun listIterator(index: Int): ListIterator<T> {
return delegate.listIterator(index).asReadOnly()
}
override fun subList(fromIndex: Int, toIndex: Int): List<T> {
return delegate.subList(fromIndex, toIndex).asReadOnly()
}
override fun toString(): String {
return "ReadOnly: ${super.toString()}"
}
override fun equals(other: Any?): Boolean {
return delegate.equals(other)
}
override fun hashCode(): Int {
return delegate.hashCode()
}
}
Along with helper extension functions to make it easy to access:
/**
* Wraps the List with a lightweight delegating class that prevents casting back to mutable type,
* specializing for the case of the RandomAccess marker interface being retained if it was there originally
*/
fun <T> List<T>.asReadOnly(): List<T> {
return this.whenNotAlreadyReadOnly {
when (it) {
is RandomAccess -> ReadOnlyRandomAccessList(it)
else -> ReadOnlyList(it)
}
}
}
/**
* Copies the List and then wraps with a lightweight delegating class that prevents casting back to mutable type,
* specializing for the case of the RandomAccess marker interface being retained if it was there originally
*/
#Suppress("UNCHECKED_CAST")
fun <T> List<T>.toImmutable(): List<T> {
val copy = when (this) {
is RandomAccess -> ArrayList<T>(this)
else -> this.toList()
}
return when (copy) {
is RandomAccess -> ReadOnlyRandomAccessList(copy)
else -> ReadOnlyList(copy)
}
}
You can see the idea and extrapolate to create the missing classes from this code which repeats the patterns for other referenced types. Or view the full code here:
https://github.com/kohesive/klutter/blob/master/core-jdk6/src/main/kotlin/uy/klutter/core/common/Immutable.kt
And with tests showing some of the tricks that allowed modifications before, but now do not, along with the blocked casts and calls using these wrappers.
https://github.com/kohesive/klutter/blob/master/core-jdk6/src/test/kotlin/uy/klutter/core/collections/TestImmutable.kt
Now we have https://github.com/Kotlin/kotlinx.collections.immutable.
fun Iterable<T>.toImmutableList(): ImmutableList<T>
fun Iterable<T>.toImmutableSet(): ImmutableSet<T>
fun Iterable<T>.toPersistentList(): PersistentList<T>
fun Iterable<T>.toPersistentSet(): PersistentSet<T>